public class MDD extends Classifier implements OptionHandler, MultiInstanceCapabilitiesHandler, TechnicalInformationHandler
@phdthesis{Maron1998, author = {Oded Maron}, school = {Massachusetts Institute of Technology}, title = {Learning from ambiguity}, year = {1998} } @article{Maron1998, author = {O. Maron and T. Lozano-Perez}, journal = {Neural Information Processing Systems}, title = {A Framework for Multiple Instance Learning}, volume = {10}, year = {1998} }Valid options are:
-D Turn on debugging output.
-N <num> Whether to 0=normalize/1=standardize/2=neither. (default 1=standardize)
Modifier and Type | Field and Description |
---|---|
static int |
FILTER_NONE
No normalization/standardization
|
static int |
FILTER_NORMALIZE
Normalize training data
|
static int |
FILTER_STANDARDIZE
Standardize training data
|
static Tag[] |
TAGS_FILTER
The filter to apply to the training data
|
Constructor and Description |
---|
MDD() |
Modifier and Type | Method and Description |
---|---|
void |
buildClassifier(Instances train)
Builds the classifier
|
double[] |
distributionForInstance(Instance exmp)
Computes the distribution for a given exemplar
|
java.lang.String |
filterTypeTipText()
Returns the tip text for this property
|
Capabilities |
getCapabilities()
Returns default capabilities of the classifier.
|
SelectedTag |
getFilterType()
Gets how the training data will be transformed.
|
Capabilities |
getMultiInstanceCapabilities()
Returns the capabilities of this multi-instance classifier for the
relational data.
|
java.lang.String[] |
getOptions()
Gets the current settings of the classifier.
|
java.lang.String |
getRevision()
Returns the revision string.
|
TechnicalInformation |
getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing
detailed information about the technical background of this class,
e.g., paper reference or book this class is based on.
|
java.lang.String |
globalInfo()
Returns a string describing this filter
|
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options
|
static void |
main(java.lang.String[] argv)
Main method for testing this class.
|
void |
setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
setOptions(java.lang.String[] options)
Parses a given list of options.
|
java.lang.String |
toString()
Gets a string describing the classifier.
|
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
public static final int FILTER_NORMALIZE
public static final int FILTER_STANDARDIZE
public static final int FILTER_NONE
public static final Tag[] TAGS_FILTER
public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class Classifier
public void setOptions(java.lang.String[] options) throws java.lang.Exception
setOptions
in interface OptionHandler
setOptions
in class Classifier
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class Classifier
public java.lang.String filterTypeTipText()
public SelectedTag getFilterType()
public void setFilterType(SelectedTag newType)
newType
- the new filtering modepublic Capabilities getCapabilities()
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class Classifier
Capabilities
public Capabilities getMultiInstanceCapabilities()
getMultiInstanceCapabilities
in interface MultiInstanceCapabilitiesHandler
Capabilities
public void buildClassifier(Instances train) throws java.lang.Exception
buildClassifier
in class Classifier
train
- the training data to be used for generating the
boosted classifier.java.lang.Exception
- if the classifier could not be built successfullypublic double[] distributionForInstance(Instance exmp) throws java.lang.Exception
distributionForInstance
in class Classifier
exmp
- the exemplar for which distribution is computedjava.lang.Exception
- if the distribution can't be computed successfullypublic java.lang.String toString()
toString
in class java.lang.Object
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Classifier
public static void main(java.lang.String[] argv)
argv
- should contain the command line arguments to the
scheme (see Evaluation)